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- W4313152037 abstract "The synthetic aperture radar (SAR) images are contaminated by noise called speckle, making the contaminated images difficult to understand and use. Since SAR images have the advantages of long range and all-weather, which can make up for the poor imaging effect of optical cameras in bad weather conditions, it is meaningful to study the de-speckling algorithm of SAR images. In order to solve the above problem, this paper proposes a method to improve the ability of removing speckles from SAR images using convolutional neural networks. And we use the attention mechanism to further improve the denoising ability based on the proposed denoising network CDNet. After experimental comparison, the speckle removal capability of CDNet proposed in this paper is better than the existing mainstream algorithms." @default.
- W4313152037 created "2023-01-06" @default.
- W4313152037 date "2022-01-01" @default.
- W4313152037 modified "2023-10-18" @default.
- W4313152037 title "Research on Speckle Reduction of SAR Image by Convolutional Neural Network" @default.
- W4313152037 doi "https://doi.org/10.25236/ajcis.2022.051115" @default.
- W4313152037 hasPublicationYear "2022" @default.
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